Target-oriented process for estimating fracture attributes from seismic data

ABSTRACT

Method for characterizing a subterranean formation includes: obtaining azimuth-dependent observed travel-times from measured seismic data; inverting observed travel-times to calculate a fracture attribute selected from the group consisting of: magnitude and orientation; identifying presence of fracture based on calculated fracture magnitude; identifying fracture direction based on calculated fracture orientation; calculating predicted travel-times; calculating differences or residual errors between observed travel-times and predicted travel-times; identifying potential fault locations based on residual errors; inverting fracture magnitude and orientation using travel-time differences between a shallower horizon to a deeper horizon of interest to minimize overburden artifacts.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a non-provisional application which claims benefitunder 35 USC §119(e) to U.S. Provisional Application Ser. No. 62/028,654filed Jul. 24, 2014, entitled “TARGET-ORIENTED PROCESS FOR ESTIMATINGFRACTURE ATTRIBUTES FROM SEISMIC DATA,” which is incorporated herein inits entirety.

FIELD OF THE INVENTION

The present invention relates generally to oil and gas exploration. Moreparticularly, but not by way of limitation, embodiments of the presentinvention include tools and methods for estimating seismic anisotropy.

BACKGROUND OF THE INVENTION

In recent years, seismic anisotropy has become an increasingly importanttopic in geophysics. Seismic anisotropy refers to a directionaldependence of seismic wave properties (e.g., velocity) in rock medium.When seismic waves propagate during seismic data acquisition, velocityof the waves may be faster in one direction while slower in anotherdirection. This directional variation can indicate certain structures inthe rock that are on the scale of the seismic wavelength. Rocks canexhibit anisotropic properties for a number of reasons including, butnot limited to, the presence of fractures, preferred orientation ofmineral grains, shape of isotropic minerals, and thin bedding ofisotropic layers. In particularly, fracture characterization is a keyattribute in optimizing hydrocarbon recovery. Understanding fracturedistribution and orientation helps identify sweet spots, especially forunconventional resources and shale plays.

Seismic data can provide indirect measure of fracture attributes.Velocity variation with azimuth (VVAZ) is a fracture detection methodused to characterize fractures by measuring velocity response of seismicwaves against varying azimuth (e.g., variation of stacking velocitieswith source-receiver azimuth). Typically, VVAZ uses prestack primarywave (P-wave) travel times from various azimuths and offsets toreconstruct normal moveout (NMO) velocity ellipse along the timedimension. Long axis of the NMO velocity ellipse corresponds to theP-wave traveling along a fracture strike direction (fast P-wavevelocity) while the short axis corresponds to the P-wave travelingperpendicular the fracture strike direction (slow P-wave velocity). Somestudies have suggested that relative ratio of the long and short axes ofthe ellipse is proportional to fracture density while fractureorientation is related to rotation of the ellipse. (Grechka andTsvankin, 1998, Jenner, 2010, and Stein et al., 2010).

Conventional techniques for estimating seismic anisotropy can sufferfrom one or more technical challenges. For example, seismic anisotropyestimation can be expensive, labor-consuming and/orcomputationally-intensive, particularly when determining azimuthalvelocities in all three dimensions of prestack seismic data. Inaddition, fracture-attribute estimations also tend to be less reliablewhen prestack seismic data have significant coherent and backgroundnoise. In general, an improper understanding of seismic anisotropy canlead to a number of issues including incorrect positions of explorationtargets and improper estimations of petroleum reservoir.

Recently, a target-oriented VVAZ method (Chiu et al, 2012) was proposed,which directly inverted horizontal transverse isotropy (HTI) magnitudeand orientation in a fracture layer. This target-oriented VVAZ methodrequires picking travel times between the top and base of the fracturelayer. The advantage of this method minimizes the overburden effects andproduces more accurate fracture estimations. Use of differential traveltimes between the top and the bottom of the target may lead to a morerobust inversion result, even for a relatively thin fracture layer.

BRIEF SUMMARY OF DISCLOSURE

The present invention relates generally to seismic exploration. Moreparticularly, but not by way of limitation, embodiments of the presentinvention include tools and methods for estimating seismic anisotropy.

One example of a method for characterizing a fracture in a subterraneanformation, the method comprising: obtaining azimuth-dependent observedtravel-times from measured seismic data; inverting observed travel-timesto calculate a fracture attribute selected from the group consisting of:magnitude and orientation; identifying presence of fracture based oncalculated fracture magnitude; identifying fracture direction based oncalculated fracture orientation; calculating predicted travel-times;calculating differences or residual errors between observed travel-timesand predicted travel-times;

identifying potential fault locations based on residual errors;inverting fracture magnitude and orientation using travel-timedifferences between a shallower horizon to a deeper horizon of interestto minimize overburden artifacts.

Another example of a method for characterizing a subterranean formation,the method comprising: obtaining observed travel-times from seismicdata; inverting, via computing processor, observed travel-times tocalculate a fracture attribute selected from the group consisting of:magnitude and orientation, wherein presence of fracture is identifiedusing calculated fracture magnitude and fracture direction is determinedusing calculated fracture orientation; calculating predictedtravel-times; calculating differences or residual errors betweenobserved travel-times and predicted travel-times; identifying potentialfault locations based on residual errors; inverting fracture magnitudeand orientation using travel-time differences between a shallowerhorizon to a deeper horizon of interest to minimize overburdenartifacts.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present invention and benefitsthereof may be acquired by referring to the follow description taken inconjunction with the accompanying drawings in which:

FIG. 1A-1B is an embodiment of the present invention: physicalinterpretation of azimuthal travel-time inversion.

FIG. 2A-2B is an embodiment of the present invention: an example ofelliptical fitting of picked travel times.

FIG. 3 is an embodiment of the present invention: an example offracture-magnitude map.

FIG. 4 is an embodiment of the present invention: an example offracture-orientation map.

FIG. 5 is an embodiment of the present invention: an example ofresidual-error map.

FIG. 6A-6B is an embodiment of the present invention: an example ofcomparing fracture-magnitude maps with and without overburden effects

DETAILED DESCRIPTION

Reference will now be made in detail to embodiments of the invention,one or more examples of which are illustrated in the accompanyingdrawings. Each example is provided by way of explanation of theinvention, not as a limitation of the invention. It will be apparent tothose skilled in the art that various modifications and variations canbe made in the present invention without departing from the scope orspirit of the invention. For instance, features illustrated or describedas part of one embodiment can be used on another embodiment to yield astill further embodiment. Thus, it is intended that the presentinvention cover such modifications and variations that come within thescope of the invention.

The present invention provides a fast, target-oriented method forestimating seismic anisotropy. While conventional methods typically relyon 3D prestack data to determine azimuthal velocity variation, thepresent invention directly estimates seismic anisotropy without havingto compute NMO velocity ellipse on the 3D prestack data. Instead, traveltimes from a targeted horizon of azimuthal (migrated or unmigrated)sectored stacks are used to directly derive physical attributes of thefracture via an inversion process.

Some of the advantages of the present invention include, but are notlimited to:

-   -   increasing signal-to-noise ratio of data to give more reliable        fracture estimations    -   reducing data dimension from 3D to a few targeted travel-time        surfaces    -   decreasing the processing time considerably to produce fracture        estimations because of reducing data dimension    -   producing horizon-consistent facture estimations    -   reducing or removing overburden effects by using the travel-time        difference or residual between azimuthal stack horizons from a        shallower horizon to the horizon of interest    -   identifying potential fault locations from residual-error map.

Other advantages will be apparent from the disclosure herein.

Equation (1) can be used to estimate seismic anisotropy:

T=T ₀+α cos 2(θ−β)   (1)

-   -   where T=azimuthal travel time,        -   T₀=isotropic travel time,        -   α=anisotropic magnitude,        -   θ=source and receiver azimuth,        -   β=fracture direction (maximum travel time).            The parameters T₀, α, and β can be solved by a least-squares            inversion. This inversion produces at least three output            maps: facture magnitude, fracture direction, and residual            fitting error.

Some embodiments provide a method for characterizing a subterraneanformation, the method comprising: obtaining observed travel-times fromseismic data; inverting observed travel-times to calculate a fractureattribute selected from the group consisting of magnitude andorientation, wherein presence of fracture is identified using calculatedfracture magnitude and fracture direction is determined using calculatedfracture orientation; calculating predicted travel-times; calculatingdifferences or residual errors between observed travel-times andpredicted travel-times; identifying potential fault locations based onresidual errors; inverting fracture magnitude and orientation usingtravel-time differences between a shallower horizon to a deeper horizonof interest to minimize overburden artifacts.

FIG. 1A-1B illustrates how azimuthal velocity variation in travel timemay relate to the presence of seismic anisotropy or fractures. Inparticular, FIG. 1 shows how equation 1 can be used to model thefracture attributes of the rock formations. If the rock is homogeneouswithout any fractures, a is zero. Thus the travel-time surface is acircle (FIG. 1A). However, if fractures are present in rock formations,the fractures cause the travel-time surface to become elliptical (FIG.1B). This method derives the fracture attributes, α and β, by modelingthe observed travel-time surface. Since α and β directly connect tofracture magnitude and direction, the mapping of both parameters from adata set provides a spatial map showing how the fractures change locallywith rock formations.

In an illustrative example, the present invention uses picked traveltimes of a common-image gather obtained from azimuthal sectored stacks(FIG. 2A) to compute the fracture attributes, α and β. Table 1, below,shows the inversion result. The average residual error is only 0.4 msecwhich is below the 2 msec sampling rate of this data set. FIG. 2B alsoshows a graphic comparison between observed travel times and traveltimes predicted from equation 1. The match between observed andpredicted values is remarkably similar.

TABLE 1 Source-receiver Input travel Predicted travel azimuth (°) time(msec) time (msec) 27 2686.6 2687.1 57 2685.7 2685.0 87 2685.9 2686.3117 2689.5 2689.6 147 2692.0 2691.6 177 2690.3 2690.4Computed fracture strike (β) is 151 degree from the North.Computed fracture magnitude (α) is 0.24.Average residual travel-time error is 0.4 msec.

Faults generally exist in rock formations. If a fault plane is presentin rock formations, it causes discontinuity of travel-time surface as afunction of azimuths within a common-image gather or a common midpointgather obtained from azimuthal sectored stacks. The discontinuity oftravel times, in turn, creates large residual errors between theobserved travel times and travel times predicted from equation 1. Thelarge residual errors from the inversion are the key to be used inidentifying potential fault locations. Table 2, below, illustrates anexample of inverting travel-time picks across a fault plane. Thetravel-time discontinuity, for example, occurs between source andreceiver azimuths of 57⁰ and 87⁰. As a result, the travel-timediscontinuity creates an average large residual error of 14.6 msec whencomparing with a much smaller residual error of 0.4 msec in Table 1. Theresidual-error map is an effective way to be used in identifying thepresence of fault locations.

TABLE 2 Source-receiver Input travel Predicted travel azimuth (°) time(msec) time (msec) 27 2340.6 2351.9 57 2340.9 2346.2 87 2373.1 2351.6117 2339.2 2361.4 147 2372.6 2367.1 177 2373.5 2362.3Computed fracture strike (β) is 148 degree from the North.Computed fracture magnitude (α) is 10.4.Average residual travel-time error is 14.6 msec.

EXAMPLE 1

FIGS. 3-5 illustrate an example of mapping inverted fracture magnitudes(FIG. 3), fracture orientations (FIG. 4) and residual fitting errors(FIG. 5). These maps can be used to highlight the fracture attributes.Fault locations can be best seen in FIG. 4 (black lines). Asillustrated, the residual-fitting-error trends (FIG. 5) followed closelywith fault locations in FIG. 4. The identification of fault locationshelps to reduce drilling risk and to optimize reservoir production.

This invention also addresses how to minimize the overburden effect thataffects the result of travel-time inversion. The seismic waves have totravel through the overburden layers first to reach a deeper targethorizon. If the travel times of overburden layers are not corrected, theoverburden will impose a footprint on the deeper horizon. The inventionalso adopts a similar approach as the target-oriented VVAZ method thatuses differential travel times between the top and the bottom of thetarget horizon. However, the invention here employs a completelydifferent mathematical model and input data when compared with thetarget-oriented VVAZ method. The approach of using differential traveltimes in equation 1 minimizes the overburden effect and produces morereliable fracture-attribute estimations. The overburden artifacts may beminimized using travel-time differences between a shallower horizon to adeeper horizon of interest. In some embodiments, the overburdenartifacts are minimized using travel-time differences between the topand bottom of a target layer.

In one embodiment, fracture magnitude and fracture orientation within anumber of layers are calculated using travel-time differences between ashallower horizon to a deeper horizon of interest. In one embodiment,fracture magnitude and fracture orientation within a target layer arecalculated using travel-time differences between the top and bottom of atarget layer.

EXAMPLE 2

FIG. 6 shows a comparison of fracture-attribute maps derived from atravel-time surface of a horizon (FIG. 6A) vs. the differential traveltimes between the top and the bottom of the target horizon (FIG. 6B).The fracture map derived from differential travel times significantlyreduces the overburden footprint and provides more reliable fractureestimations that are related to the fractures of the target horizon butnot the overburden artifacts.

According to one embodiment, the present invention can be used to scanfor potential fault locations. If the azimuthal travel-time surfaceschange abruptly across a fault plane, the travel-time changes alsocreate large residual fitting errors associated with a fault location.

Azimuthal velocity variation in travel time can be a good indicator ofthe presence of seismic anisotropy or fractures. According to one ormore embodiments, the present invention provide a method that utilizestravel times from target horizons of azimuthal sectored stacks to invertfor fracture attributes.

The target-oriented travel-time inversion provides a fast,target-oriented method for estimating seismic anisotropy by usingazimuthal (migrated or unmigrated) sectored stacks instead of prestackseismic data. Since this method bases on picking travel times on seismichorizons, it produces horizon-consistent facture estimations. Theresidual error map derived from this invention provides an alternativeway to identify potential fault locations. In addition, this inventionalso addresses how to minimize the overburden effect that affects theresult of travel-time inversion. It utilizes the differential traveltimes between the top and the bottom of the target horizon to estimatefracture attributes. The fracture map derived from the differentialtravel times gives more reliable fracture estimations that are relatedto the fractures of target horizon but not the overburden artifacts.

Although the systems and processes described herein have been describedin detail, it should be understood that various changes, substitutions,and alterations can be made without departing from the spirit and scopeof the invention as defined by the following claims. Those skilled inthe art may be able to study the preferred embodiments and identifyother ways to practice the invention that are not exactly as describedherein. It is the intent of the inventors that variations andequivalents of the invention are within the scope of the claims whilethe description, abstract and drawings are not to be used to limit thescope of the invention. The invention is specifically intended to be asbroad as the claims below and their equivalents.

REFERENCES

All of the references cited herein are expressly incorporated byreference. The discussion of any reference is not an admission that itis prior art to the present invention, especially any reference that mayhave a publication data after the priority date of this application.Incorporated references are listed again here for convenience:

-   -   1. Stephen K. Chiu, Jason A Stein, Jack Howell, Samik Sil,        Michael Davidson, and Jeff Malloy, 2012, Validate        target-oriented VVAZ with formation microimaging, SEG Technical        Program Expanded Abstracts: pp. 1-5.    -   2. Grechka, V., and I. Tsvankin, 1998, 3-D description of normal        moveout in anistropic inhomogeneous media: Geophysics, 63,        1079-1092.    -   3. Jenner, E., 2010, Modelling azimuthal NMO in laterally        heterogeneous HTI media: First Break volume 28, No. 9, 89-94.    -   4. Stein, J., A., R. Wojslaw, T. Langston, and S. Boyer, 2010,        Wide-azimuth land processing: Fracture detection using offset        vector tile technology: The leading edge, Nov., 1328-1337.

1. A method for characterizing a subterranean formation, the methodcomprising: a) obtaining azimuth-dependent observed travel-times frommeasured seismic data; b) inverting observed travel-times to calculate afracture attribute selected from the group consisting of: magnitude andorientation; c) identifying presence of fracture based on calculatedfracture magnitude; d) identifying fracture direction based oncalculated fracture orientation; e) calculating predicted travel-times;f) calculating differences or residual errors between observedtravel-times and predicted travel-times; g) identifying potential faultlocations based on residual errors; h) inverting fracture magnitude andorientation using travel-time differences between a shallower horizon toa deeper horizon of interest to minimize overburden artifacts.
 2. Themethod of claim 1 wherein the fracture magnitude (α) and fractureorientation (β) are calculated using equation T=T₀+α cos 2(θ−β), whereinT is azimuthal travel time, T₀ is isotropic travel time, and θ is sourceand receiver azimuth.
 3. The method of claim 1 wherein the observedtravel-times were obtained from a common-image gather from azimuthalsectored stacks.
 4. The method of claim 3 wherein the azimuthal sectoredstack is migrated or unmigrated.
 5. The method of claim 1 wherein thepredicted travel-times are calculated using equation T=T₀+α cos 2(θ−β).6. The method of claim 5 wherein the fault location is indicated bylargest residual difference between observed and predicted travel-times.7. The method of claim 1 wherein the fracture magnitude and fractureorientation within a number of layers are calculated using travel-timedifferences between a shallower horizon to a deeper horizon of interest.8. The method of claim 1 wherein the fracture magnitude and fractureorientation within a target layer are calculated using travel-timedifferences between the top and bottom of a target layer.
 9. The methodof claim 7 wherein overburden artifacts are minimized using travel-timedifferences between a shallower horizon to a deeper horizon of interest.10. The method of claim 8 wherein overburden artifacts are minimizedusing travel-time differences between the top and bottom of a targetlayer.
 11. A method for characterizing a subterranean formation, themethod comprising: a) obtaining observed travel-times from seismic data;b) inverting, via computing processor, observed travel-times tocalculate a fracture attribute selected from the group consisting of:magnitude and orientation, wherein presence of fracture is identifiedusing calculated fracture magnitude and fracture direction is determinedusing calculated fracture orientation; c) calculating predictedtravel-times; d) calculating differences or residual errors betweenobserved travel-times and predicted travel-times; e) identifyingpotential fault locations based on residual errors; f) invertingfracture magnitude and orientation using travel-time differences betweena shallower horizon to a deeper horizon of interest to minimizeoverburden artifacts.
 12. The method of claim 11 wherein the fracturemagnitude (α) and fracture orientation (β) are calculated using equationT=T₀+α cos 2(θ−β), wherein T is azimuthal travel time, T₀ is isotropictravel time, and θ is source and receiver azimuth.
 13. The method ofclaim 1 wherein the observed travel-times were obtained from acommon-image gather from azimuthal sectored stacks.
 14. The method ofclaim 13 wherein the azimuthal sectored stack is migrated or unmigrated.15. The method of claim 1 wherein the predicted travel-times arecalculated using equation T=T₀+α cos 2(θ−62 ).
 16. The method of claim15 wherein the fault location is indicated by largest residualdifference between observed and predicted travel-times.
 17. The methodof claim 11 wherein the fracture magnitude and fracture orientationwithin a number of layers are calculated using travel-time differencesbetween a shallower horizon to a deeper horizon of interest.
 18. Themethod of claim 11 wherein the fracture magnitude and fractureorientation within a target layer are calculated using travel-timedifferences between the top and bottom of a target layer.
 19. The methodof claim 17 wherein overburden artifacts are minimized using travel-timedifferences between a shallower horizon to a deeper horizon of interest.20. The method of claim 18 wherein overburden artifacts are minimizedusing travel-time differences between the top and bottom of a targetlayer.